Research Engineer - State Estimation and Visual Odometry (ML+classic)

At Flexion, we're building the intelligence layer powering the next generation of humanoid robots. Our mission is to accelerate the transition from fragile prototypes to real-world deployment of humanoids. 

We are looking for a computer vision and sensor fusion expert to strengthen our team in Zurich.

The goal of this position is to develop next-generation robust, reliable state estimation solutions for humanoid robots, primarily using proprioceptive and visual sensors.

We are looking for an expert in optimization-based and filtering-based state estimation and sensor fusion for robotic systems, ideally with a focus on visual odometry. Moreover, the person should have a strong understanding of modern machine learning methods, including sequence-to-sequence learning, autoregressive, and diffusion models. Good knowledge of recent end-to-end learned odometry and motion estimation solutions is beneficial.

Particularly:

• PhD or master's degree in computer vision or robotics with relevant experience.
• Multi-year experience (either PhD or industry) in visual inertial odometry (VIO) and motion estimation.
• Excellent knowledge of efficient C++ programming and real-time deployment.
• Experience with Python, PyTorch, and the training of deep neural networks.
• Hands-on experience working with robotic systems and/or AR/VR devices.
  

We are looking for a person who enjoys working in a team in a dynamic, fast-moving environment and is able and willing to take ownership of projects and decisions.

We at Flexion Robotics (flexion.ai) are a young company in Zurich working on the next generation of humanoid robot software to enable robots to perform useful tasks autonomously.

We work dynamically and move fast. Every new employee at this stage will have significant ownership of their current project.

We offer a competitive remuneration in the form of a competitive base salary and additional components/benefits depending on the specific role and the experience of the applicant.